Testing the significance of spatio-temporal teleconnection patterns

Jaya Kawale, Singdhansu B Chatterjee, Dominick Ormsby, Karsten Steinhaeuser, Stefan Liess, Vipin Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Dipoles represent long distance connections between the pressure anomalies of two distant regions that are negatively correlated with each other. Such dipoles have proven important for understanding and explaining the variability in climate in many regions of the world, e.g., the El Nino climate phenomenon is known to be responsible for precipitation and temperature anomalies over large parts of the world. Systematic approaches for dipole detection generate a large number of candidate dipoles, but there exists no method to evaluate the significance of the candidate teleconnections. In this paper, we present a novel method for testing the statistical significance of the class of spatio-temporal teleconnection patterns called as dipoles. One of the most important challenges in addressing significance testing in a spatio-temporal context is how to address the spatial and temporal dependencies that show up as high autocorrelation. We present a novel approach that uses the wild bootstrap to capture the spatio-temporal dependencies, in the special use case of teleconnections in climate data. Our approach to find the statistical significance takes into account the autocorrelation, the seasonality and the trend in the time series over a period of time. This framework is applicable to other problems in spatio-temporal data mining to assess the significance of the patterns.

Original languageEnglish (US)
Title of host publicationKDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages642-650
Number of pages9
DOIs
StatePublished - Sep 14 2012
Event18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 - Beijing, China
Duration: Aug 12 2012Aug 16 2012

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Other

Other18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012
CountryChina
CityBeijing
Period8/12/128/16/12

Fingerprint

Autocorrelation
Testing
Data mining
Time series
Temperature

Keywords

  • significance testing

Cite this

Kawale, J., Chatterjee, S. B., Ormsby, D., Steinhaeuser, K., Liess, S., & Kumar, V. (2012). Testing the significance of spatio-temporal teleconnection patterns. In KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 642-650). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). https://doi.org/10.1145/2339530.2339634

Testing the significance of spatio-temporal teleconnection patterns. / Kawale, Jaya; Chatterjee, Singdhansu B; Ormsby, Dominick; Steinhaeuser, Karsten; Liess, Stefan; Kumar, Vipin.

KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012. p. 642-650 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kawale, J, Chatterjee, SB, Ormsby, D, Steinhaeuser, K, Liess, S & Kumar, V 2012, Testing the significance of spatio-temporal teleconnection patterns. in KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 642-650, 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012, Beijing, China, 8/12/12. https://doi.org/10.1145/2339530.2339634
Kawale J, Chatterjee SB, Ormsby D, Steinhaeuser K, Liess S, Kumar V. Testing the significance of spatio-temporal teleconnection patterns. In KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012. p. 642-650. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). https://doi.org/10.1145/2339530.2339634
Kawale, Jaya ; Chatterjee, Singdhansu B ; Ormsby, Dominick ; Steinhaeuser, Karsten ; Liess, Stefan ; Kumar, Vipin. / Testing the significance of spatio-temporal teleconnection patterns. KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012. pp. 642-650 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).
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